Machine Learning (AI) Engineer (Hybrid)
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Key skills for this role
About the Role
Hire Feed is hiring a Machine Learning Engineer for a client to develop and deploy machine learning models that power core product features. The role involves collaborating with cross-functional teams to design scalable AI solutions.
Key Skills for This Role
Responsibilities
- Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch frameworks
- Develop and maintain data pipelines to ensure high quality input for model training and evaluation
- Implement MLOps practices to streamline model deployment, monitoring, and version control
- Collaborate with data scientists and software engineers to integrate AI capabilities into production systems
- Conduct performance benchmarking and A/B testing to validate model accuracy and business impact
Requirements
- Proficiency in Python, TensorFlow, and PyTorch for model development and training
- Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for deployment and monitoring
- Strong background in data preprocessing, feature engineering, and model evaluation metrics
- Familiarity with cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure
- Knowledge of software engineering best practices, including version control (Git) and CI/CD pipelines
Full Job Posting
Role Overview
- We are hiring for one of our clients, seeking an AI/ML Engineer to develop and deploy machine learning models that power core product features.
- The role involves collaborating with cross functional teams to design scalable AI solutions that enhance user experience and operational efficiency.
Key Responsibilities
- Design, train, and optimize machine learning models using Python, TensorFlow, and PyTorch frameworks.
- Develop and maintain data pipelines to ensure high quality input for model training and evaluation.
- Implement MLOps practices to streamline model deployment, monitoring, and version control.
- Collaborate with data scientists and software engineers to integrate AI capabilities into production systems.
- Conduct performance benchmarking and A/B testing to validate model accuracy and business impact.
Required Skills & Qualifications
- Proficiency in Python, TensorFlow, and PyTorch for model development and training.
- Experience with MLOps tools such as MLflow, Kubeflow, or SageMaker for deployment and monitoring.
- Strong background in data preprocessing, feature engineering, and model evaluation metrics.
- Familiarity with cloud platforms (AWS, GCP, or Azure) for scalable AI infrastructure.
- Knowledge of software engineering best practices, including version control (Git) and CI/CD pipelines.
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